The Impact of Pandemic Management Strategies on Staff Mental Health, Work Behaviours, and Resident Care in One Long-Term Care Facility in British Columbia: A Mixed Method Study

Context: To slow the spread of COVID-19 within the Canadian long-term residential care (LTRC) sector, a series of pandemic management strategies were introduced, including restricted visitation and single site employment. These strategies were enacted to prevent and control infection, resulting in unknown impact on direct care staff and staff capacity to deliver quality care or service. Objective: To explore staff reports of outcomes associated with LTRC pandemic management strategies, particularly their impact on LTRC staff mental health, work behaviours and quality of care or service provision. Method: This was a case study using mixed methods including a longitudinal survey and interviews with staff from one LTRC site in British Columbia. Survey data from 68 staff who participated in both survey times were analyzed using regressions with relative weight analysis. Semi-structured interviews were conducted with 26 LTRC staff and analyzed using content analysis. Findings: Survey data demonstrated that staff perceived the sick time policy and staffing levels as the most inadequate pandemic management strategies. Survey data also showed the visitation policy, the sick time policy and the single site employment policy were most significantly associated with negative outcomes to staff mental health, work behaviours and quality of care or service delivery. Qualitative data suggested connections between these policies and inadequate staffing levels and heavy workloads. Limitations: The study design along with the low response rate and the small sample size limits the generalizability of the findings to other settings. Implications: The development and implementation of pandemic management strategies must be informed by and give consideration to working conditions of LTRC staff including long standing systemic issues such as staffing shortages and heavy workloads. © 2022 The Author(s).